Top PDF An Unique Edge Preserving Noise Filtering Technique for Impulse Noise Removal

An Unique Edge Preserving Noise Filtering Technique for Impulse Noise Removal

An Unique Edge Preserving Noise Filtering Technique for Impulse Noise Removal

Image de-noising is the technique to reduce noises from corrupted images. The aim of the image de- noising is to improve the contrast of the image or perception of information in images for human viewers or to provide better output for other automated image processing techniques. This paper presents a new approach for color image de-noising with Fuzzy Filtering techniques using centroid method for defuzzification. It preserves any type of edges (including tiny edges) in any direction. The experimental result shows the effectiveness of the proposed method.
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FPGA IMPLEMENTATION AND ANALYSIS OF IMPULSE NOISE REDUCTION IN IMAGES

FPGA IMPLEMENTATION AND ANALYSIS OF IMPULSE NOISE REDUCTION IN IMAGES

Chen et al. (2010) has proposed low cost VLSI implementation for efficient removal of impulse noise. Their extensive experimental results show that the proposed technique preserves the edge features and obtains excellent performances in terms of quantitative evaluation and visual quality. Smolka (2012) proposed a new approach for removing impulse noise in color images. The design used the vector median filter and is based on the weighting of the dissimilarity measures between pixels contained in the local filtering window. The weights assigned to each color sample are decreasing functions of their ranks in an ordered sequence, while the ordering is based on the distance between a given pixel and its neighbours. Extensive experiments proved that their filtering design efficiently removed the impulse noise in color images while enhancing their edges. This unique feature can be utilized in any application in which noise removal combined with edge enhancement is needed.
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A Decision tree and Conditional Median Filter Based Denoising  for impulse noise in images

A Decision tree and Conditional Median Filter Based Denoising for impulse noise in images

this is done by two steps. First step detection then filtering. Non linear filtering techniques are implemented widely because of their superior performance in removing salt and pepper noise and also preserving fine details of image. There are many works on the restoration of images corrupted by salt and pepper noise. The median filter was once the most popular non linear filter for removing impulse noise, because of its good denoising power and computational efficiency. Median filters are known for their capability to remove impulse noise as well as preserve the edges. In image processing [2],[3] many methods have been developed for the removal of impulse noise in images. The standard median filter [10] is such technique for the removal of image impulse noise. This technique has the disadvantage of poor image quality obtained after the de-noising. This might blur the image because it modifies both noisy and noisy free pixels. In order to overcome this disadvantage of standard median filter new technique switching median filter have been introduced. The switching median filter consists of two main steps an impulse detector to detect the noisy pixels and an impulse noise filter filters the noisy pixels. The advantage of this technique is that it effectively removes the noisy pixels only rather than the whole pixels of the image to avoid causing damage on noisy-free pixels. Luo proposed another technique An Alpha Trimmed Mean Based Method (ATMBM) [11]. It uses alpha trimmed mean for impulse noise detection and the detected noisy pixel values is replaced by the original detected value and the median value of its local window. A Differential Rank Impulse Detector (DRID) was presented in [4]. In DRID impulse detector works on the comparison
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Image Fusion Technique for Impulse Noise Removal in Digital Images using Empirical Mode Decomposition

Image Fusion Technique for Impulse Noise Removal in Digital Images using Empirical Mode Decomposition

In this paper, an image fusion technique using BEMD for impulse noise reduction in digital images is presented. The proposed technique helps to attain high quality images. Images of an object or scene, captured by sensors undergo filtering using different filtering algorithms individually and these de-noised images are fused by the proposed technique. The Fusion using BEMD provides superior performance in removing the noise, while preserving the fine image details and edges. The proposed method is simple and can be used for real-time imaging applications.
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Advanced Impulse Detection & Reduction Based on Multimodal Filter

Advanced Impulse Detection & Reduction Based on Multimodal Filter

Images are often corrupted by impulse noise due to a noisy sensor or channel transmission errors. The goal of impulse noise removal is to suppress the noise while preserving the integrity of edge and detail information. A fundamental problem in image processing is to effectively remove noise from an image while keeping its features intact, but nature of problem depends upon the type of noise in the image. Basically there are two types of Impulse Noise. They are Random Value Impulse Noise and Fixed Value Impulse Noise. In Random value impulse noise the noise pixels are distributed based on Random Distribution. In Fixed value the noise pixels takes a value of 0 and 255 i.e., the minimum and maximum value in the grey scale. Digital filters are widely used in many applications in signal processing, communications, control, electrical and biomedical systems.
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NOISE REMOVAL TECHNIQUES FOR MICROWAVE REMOTE SENSING RADAR DATA AND ITS EVALUATION

NOISE REMOVAL TECHNIQUES FOR MICROWAVE REMOTE SENSING RADAR DATA AND ITS EVALUATION

Using these, different denoising filters can be designed for various types of images. In the case of radar data as the noise is not Gaussian in nature, initially scientists attempted to convert the signal to an additive one, by taking logarithm, the used the denoising techniques applicable to such noise, and then again reverted back. This was not suffiecient. Using thresholding techniques[5], good results were obtained for additive noise. Applying the same techniques on converted signals did not give appreciable results. On the other hand, Daubechies wavelet coefficients of different tap sizes yield results which are comparable to standard noise removal filters of [1][2]. Here we have attempted some of the techniques on different types of data sets.
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Noise Analysis of Ultra High Speed SiGe BiCMOS Track and Hold Amplifier for Fiber Optic Equalizer

Noise Analysis of Ultra High Speed SiGe BiCMOS Track and Hold Amplifier for Fiber Optic Equalizer

Traditional circuit simulators such as HSPICE or SWIT- CAP have limitations in noise analysis by using a transistor-level description for the switched circuit. Spec- treRF circuit simulator is capable of performing small signal analyses such as AC and noise about a periodic operating point and so can directly measure the transfer and noise characteristics of the switched circuit using a transistor-level description.

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Continuous Scanning Technique with Barkhausen Magnetic Noise for Carbon Steel Sheets

Continuous Scanning Technique with Barkhausen Magnetic Noise for Carbon Steel Sheets

From the analysis of Figs. 7-11(5 Hz) and 12-16 (10 Hz) it is observed that the technique can detect the location of the plastic deformation with all five speeds used. It can also be observed that the speed variation within the 14 to 25 mm/s range does not have a significant influence on detection. Therefore, higher speeds can be used, which results in an advantage of the technique when considering its application in the industrial area.

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Removal of Salt and Pepper Noise through Unsymmetric Trimmed Median Filter

Removal of Salt and Pepper Noise through Unsymmetric Trimmed Median Filter

-----------------------------------------------------------------ABSTRACT---------------------------------------------------------------- Here a modified decision based unsymmetrical trimmed median filter algorithm for the restoration of gray scale, and colour images that are highly corrupted by salt and pepper noise is proposed. This algorithm replaces the noisy pixel by trimmed median value when other pixel values, 0’s and 255’s are present in the selected window and when all the pixel values are 0’s and 255’s then the noise pixel is replaced by mean value of all the elements present in the selected window. This proposed algorithm shows better results than the Standard Median Filter (MF), Decision Based Algorithm (DBA), Modified Decision Based Algorithm (MDBA), and Progressive Switched Median Filter (PSMF). The proposed algorithm is tested against different gray scale and colour images and it gives better Peak Signal-to-Noise Ratio (PSNR) and Image Enhancement Factor (IEF).
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J. Aerosp. Technol. Manag.  vol.3 número3

J. Aerosp. Technol. Manag. vol.3 número3

means to safely conduct a watercraft or an aircraft from one point to another, which is a complex guidance process that enables long journeys with the goal to reach a speciic place safely. The safety aspect should also include issues related to sound emission, once they can cause not only discomfort, but also damage to those who are continuously exposed to this type of noise. It is possible to say that the study of airport noise is really relevant worldwide, especially regarding issues related to aircraft noise. As to this aspect, the study concerning the sensitivity analysis is signiicantly helpful, since it allows identifying which areas of the noise curves have varied more from the changes in the aircraft movements at a speciic airport.
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Wavelet Shrinkage in Noise Removal of Hyperspectral Remote Sensing Data

Wavelet Shrinkage in Noise Removal of Hyperspectral Remote Sensing Data

Several methods have been used to smooth noisy signals, including the Fourier transform, the Savitzky- Golay local polynomial, the mean filter, Gaussian functions, and so on. However, these methods have characteristics that could reduce their effectiveness in dealing with noisy signals. In recent years, a new method known as wavelet shrinkage has been introduced to the scientific community. It is said to offer a more efficient and statistically rigorous approach to signal processing. Among the advantages of the wavelet shrinkage method is that it can be used to reduce the level of noise while preserving the significant features of the original data [1] . However, practical guidance on the use of the wavelet- based denoising is hard to find [2] and the use of wavelet transform in the analysis of hyperspectral data is very limited [3] .
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Random-valued Impulse Noise Reduction by MST-based Method for Color Image

Random-valued Impulse Noise Reduction by MST-based Method for Color Image

A test image is generated artificially, and is then applied to VMF, to Sun’s switching median filter (SSMF) [1], to robust switching vector median filter (RSVM) [5], and to the MST-based method (SVMF-MST). Figure 3(a) shows a color image (65 × 65 pixels, 8 bit/pixel for each RGB channel) including line structures for testing. In the im- age, the colors of the line parts are generated from com- binations of brightness values {40, 160} for each chan- nel. Figure 3(b) shows a noisy test image corrupted by random-valued impulse noise with p = 0.01. Fig- ures 3(c), 3(d), 3(e), and 3(f) show the filtering results by VMF, SSMF, RSVM, and SVMF-MST, respectively. The threshold of SSMF is given by the following equation [6], Θ = 0.314P 2 − 5.94P + 57.7. Here, P represents the
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Brake Noise

Brake Noise

O interesse no tema Brake Noise advém da pressão da indústria automóvel em compreender o mecanismo que origina o ruído no sistema de travagem, sendo este uma das maiores incidências de reclamações por parte de clientes, trazendo problemas como insatisfação do passageiro e custos de garantia. Estudos com o intuito de prever e eliminar este ruído têm vindo a ser conduzidos desde a primeira conceção deste sistema. Apesar do seu avanço, a previsão do ruído de travão continua num impasse pois nem todos os mecanismos e interações são conhecidos devido à sua natureza altamente efusiva, transiente e muitas vezes não repetível. Tal é causado pela natureza complexa da interação (linear e não linear) dos componentes do sistema de travagem (disco, pastilhas, corpo, ponte, etc.) e da interdependência dos parâmetros (como condições operacionais e de contato, propriedades dos materiais, desgaste, etc.). Daí a pertinência na compreensão dos parâmetros mais influentes (alguns já conhecidos) com o propósito de estudar a sua potencial influência na redução, ou até mesmo eliminação, do ruído proveniente do sistema de travagem [1, 2].
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Periodic Noise Suppression from ECG Signal using  Novel Adaptive Filtering Techniques

Periodic Noise Suppression from ECG Signal using Novel Adaptive Filtering Techniques

Abstract- Electrocardiogram signal most commonly known recognized and used biomedical signal for medical examination of heart. The ECG signal is very sensitive in nature, and even if small noise mixed with original signal, the various characteristics of the signal changes, Data corrupted with noise must either filtered or discarded, filtering is important issue for design consideration of real time heart monitoring systems.

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A influência da forma urbana na propagação do ruído urbano

A influência da forma urbana na propagação do ruído urbano

Abstract: - The urban form affects directly the natural habitats, ecosystems and the different species. Indirectly the urban form influences the behavior of the trajectory, which in turn affects the air quality, the global climate and of course the noise propagation. This paper seeks to address the problems of the urban environment as an area of interaction between urban forms and urban noise. This interaction is intended to be monitored by urban indicators, comparing the effects of noise propagation in model of urban forms. The model of noise prediction (NMPB96), allowed to develop studies about noise in facades (Ld, level of noise during the day), resulting in colors associated to noise categories. The study will allow the creation of different scenarios and foresee still in the draft fase, the facades exposed to a higher noise level. The effects of noise in facades can be then minimized in advance, by adjusting the layout of their typology.
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NOISE ATTENUATION IN SEISMIC REFLECTION DATA COMBINING EMPIRICAL MODE DECOMPOSITION AND SVD FILTERING

NOISE ATTENUATION IN SEISMIC REFLECTION DATA COMBINING EMPIRICAL MODE DECOMPOSITION AND SVD FILTERING

ABSTRACT. Noises are common events in seismic reflection that have very striking features in the seismograms, hindering the data processing and interpretation. The attenuation of seismic noise is a challenge. In general frequency filters are employed, but they often do not show good results. The characteristic of noise depends mainly on the type of data we are working. In land data, the most common is the ground roll, that has low frequencies and high amplitudes whereas in marine data (on a shallow water acquisition), head waves and harmonic modes are linear and dispersive events that mask part of the interest reflections, influencing the delimitation of lithological layers. In this study, we used the methods of Empirical Mode Decomposition (EMD) and Singular Value Decomposition (SVD) in order to mitigate some types of noise in seismic reflection and create alternatives to interpretation based on different frequency content present in seismic section. This new approach consists in relating the operation mode of each method with the main features of the noise, resulting in a technique that can identify and mitigate the unwanted event from the seismograms, trying always to preserve or enhance the interest signal. To test the effectivity of this new approach, were used land seismic data from the Tacutu Basin and marine from the Grane oilfield area, Norway.
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Link Between the Seismic Events and the Different Seismic Precursor Phenomena

Link Between the Seismic Events and the Different Seismic Precursor Phenomena

Abstract: This article presents an analysis of the earthquake prediction methods, highlighting mainly the VLF and LF electromagnetic waves seismic precursors’ monitoring method and the correlation among these in order to obtain a more precise result. It is well known the fact that there are lots of links between the seismic events occurrence and different phenomena that predict their occurrence, such as the electromagnetic field, Earth movement, gaseous content of radon and hydrogen within the soil, or within the underground waters. This paper aims to demonstrate the close link between the seismic events and the electromagnetic wave propagation anomalies, which are recorded before the advent of an earthquake.
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CRISPR Content Correlates with the Pathogenic Potential of Escherichia coli.

CRISPR Content Correlates with the Pathogenic Potential of Escherichia coli.

One of the most important stages in image processing applications is the noise filtering. The importance of image sequence processing is constantly growing with the ever increasing use of digital television and video systems in consumer, commercial, medical, and communicational applications. Image filtering is not only used to improve image quality but also is used as a preprocessing stage in many applications including image encoding, pattern recognition, image compression and target tracking, to name a few. This preprocessing stage is essential in most of the image-processing algorithm and improper noise filtering may result in inappropriate or even false outcome. Different methods have been proposed for the purpose of noise filtering. However these methods can be categorized in two categories as follows:
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Noise Management at Work

Noise Management at Work

• reduction at the source or in the path – using mufflers or silencers on exhausts, reducing cutting, fan, or impact speeds, dynamically balancing rotating components, reducing fluid flow speeds and turbulence, absorbing foam or fibreglass on reflective surfaces to reduce reverberation, sealing around doors and windows , shields to reflect and redirect noise (especially high frequencies), lining or wrapping of pipes and ducts and use flexible pipes, or preventing impact and collision during manual and mechanical materials handling (e.g., using soft rubber or plastic to receive hard impacts);
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Touchstone® File Format Specification

Touchstone® File Format Specification

The [Matrix Format] keyword and argument specify whether an entire matrix or a subset of all matrix elements is given for single-ended data. The latter case is applicable to symmetric matrices for which either only the lower triangular part (including the diagonal), or only the upper triangular part (including the diagonal) is included. This assumption is most appropriate for interconnects. Note that all ports are always represented, but the format for the data takes advantage of symmetry to reduce the overall file size. The [Matrix Format] keyword, in brackets as shown, shall be followed by one of three possible string arguments: “Full”, “Lower”, or “Upper”.
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